Translation initiation of leaderless and polycistronic transcripts in mammalian mitochondria

Abstract The synthesis of mitochondrial OXPHOS complexes is central to cellular metabolism, yet many molecular details of mitochondrial translation remain elusive. It has been commonly held view that translation initiation in human mitochondria proceeded in a manner similar to bacterial systems, with the mitoribosomal small subunit bound to the initiation factors, mtIF2 and mtIF3, along with initiator tRNA and an mRNA. However, unlike in bacteria, most human mitochondrial mRNAs lack 5′ leader sequences that can mediate small subunit binding, raising the question of how leaderless mRNAs are recognized by mitoribosomes. By using novel in vitro mitochondrial translation initiation assays, alongside biochemical and genetic characterization of cellular knockouts of mitochondrial translation factors, we describe unique features of translation initiation in human mitochondria. We show that in vitro, leaderless mRNA transcripts can be loaded directly onto assembled 55S mitoribosomes, but not onto the mitoribosomal small subunit (28S), in a manner that requires initiator fMet-tRNAMet binding. In addition, we demonstrate that in human cells and in vitro, mtIF3 activity is not required for translation of leaderless mitochondrial transcripts but is essential for translation of ATP6 in the case of the bicistronic ATP8/ATP6 transcript. Furthermore, we show that mtIF2 is indispensable for mitochondrial protein synthesis. Our results demonstrate an important evolutionary divergence of the mitochondrial translation system and further our fundamental understanding of a process central to eukaryotic metabolism.


Preparation of mitoribosomal subunits and reassociated 55S for initiation studies
Human mitoribosomes were purified according to previously described protocols (Spremulli, 2007) with modifications.
Briefly, HEK293 cells were pelleted by centrifugation at 1000 g for 10 min and washed with cold PBS. The pellet was then dissolved in Swelling Buffer (25 mM HEPES/KOH pH 7.5, 100 mM KCl, 20 mM Mg(OAc)2, 2 mM DTT) for 20 min at 4˚C. Afterwards, the buffer was supplemented with sucrose and mannitol to a final concentration of 70 mM sucrose and 210 mM mannitol, and the cells were disrupted with 10 strokes in a 100 mL glass homogenizer.
Nuclei and cell debris were pelleted by centrifugation at 1000 g for 10 min, and crude  Supplementary Fig. 1D, III), and the samples corresponding to the monosome were pooled and centrifuged in a TLA100.4 rotor for 16 h at 55000 rpm.

Mass spectrometry analysis of mtIF3 FLAG immunoprecipitations
Identification and quantification of co-immunoprecipitated proteins was carried out as described previously 41 . Peptides were separated on a 25 cm, 75 µm internal diameter PicoFrit analytical column (New Objective) packed with 1.9 µm ReproSil-Pur 120 C18-AQ media (Dr. Maisch,) using an EASY-nLC 1200 (Thermo Fisher Scientific). The column was maintained at 50°C. Buffer A and B were 0.1% formic acid in water and 0.1% formic acid in 80% acetonitrile.
Peptides were separated on a segmented gradient from 6% to 31% buffer B for 45 min and from 31% to 50% buffer B for 5 min at 200 nl / min. Eluting peptides were analyzed on QExactive HF mass spectrometer (Thermo Fisher Scientific). Peptide precursor m/z measurements were carried out at 60000 resolution in the 300 to 1800 m/z range. The ten most intense precursors with charge state from 2 to 7 only were selected for HCD fragmentation using 25% normalized collision energy. The m/z values of the peptide fragments were measured at a resolution of 30000 using a minimum AGC target of 2e5 and 80 ms maximum injection time. Upon fragmentation, precursors were put on a dynamic exclusion list for 45 sec. The raw data were analyzed with MaxQuant version 1.6.1.0 43 using the integrated Andromeda search engine 44 .
Peptide fragmentation spectra were searched against the canonical sequences of the human reference proteome (proteome ID UP000005640, downloaded September 2018 from UniProt).
Methionine oxidation and protein N-terminal acetylation were set as variable modifications; cysteine carbamidomethylation was set as fixed modification. The digestion parameters were set to "specific" and "Trypsin/P," The minimum number of peptides and razor peptides for protein identification was 1; the minimum number of unique peptides was 0. Protein identification was performed at a peptide spectrum matches and protein false discovery rate of 0.01. The "second peptide" option was on. Successful identifications were transferred between the different raw files using the "Match between runs" option. Label-free quantification (LFQ) 45 was performed using an LFQ minimum ratio count of two. LFQ intensities were filtered for at least two valid values in at least one group and imputed from a normal distribution with a width of 0.3 and down shift of 1.8. Protein quantification was performed using limma 46 . Mitocarta 47 annotations were added using the primary gene name and the first of the gene name synonyms of the oldest Uniprot ID with the highest number of peptides.
To facilitate the direct comparison of mitochondrial gene expression in WT and mtIF3 KO 1 libraries, counts of mitochondrial ribosome-protected fragments (mt-RPFs) per gene in a given library were expressed as a percentage of total mtRPFs in that library. Only mtRPFs with 5′ ends mapping in the positive-sense orientation between the first nucleotide of the start codon and 30 nt 5′ of the stop codon were counted, and regions where ORFs overlap in the bicistronic ATP8/ATP6 and ND4L/ND4 transcripts were excluded from the expression calculations due to ambiguous assignment of RPFs to ORFs in these regions. Supplementary Fig. 4) Brightness-Gated Two-Color Coincidence Detection (BTCCD) is a further development of classical Two Color Coincidence Detection (TCCD) method 1 . It is used for quantification of fraction of associated and dissociated molecules in solution by means of dual-color single molecule confocal fluorescence detection. Detailed description of BTCCD analysis can be found in 2 . In brief, due to incomplete overlap of confocal volumes for different laser wavelength, molecule carrying both red and green fluorophores can be detected as singlelabeled. In BTTCD analysis it is assumed that brighter bursts are collected from the molecules that spent longer time in the confocal volume or/and traveled through the center. Such bursts have higher probability to travel through both green and red confocal volumes. Coincidence fraction is calculated for varying range of brightness threshold nbr. Increasing nbr, calculated coincidence fraction will as well increase, until it saturates when only molecule trajectories that touched both volumes are left. Resulting coincidence value represents the real fraction of molecules that carry both red and greed fluorophores. Coincidence fraction for higher nbr corresponds to the increased overlap of two confocal volumes and, therefore, more accurate value. However, precision of the determined coincidence fraction decreases because the number of bursts entering analysis is lower for higher nbr. Optimal nbr, opt is defined as an intersection point between relative accuracy and relative precision. Most reliable coincidence fraction is defined as a coincidence fraction for nbr, opt.